Asymmetric Time Aggregation and its Potential Benefits for Forecasting Annual Data

Kunst, Robert M. and Franses, Philip Hans (July 2010) Asymmetric Time Aggregation and its Potential Benefits for Forecasting Annual Data. IHS Economics Series 252

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Abstract or Table of Contents

Abstract: For many economic time-series variables that are observed regularly and frequently, for example weekly, the underlying activity is not distributed uniformly across the year. For the aim of predicting annual data, one may consider temporal aggregation into larger subannual units based on an activity time scale instead of calendar time. Such a scheme may strike a balance between annual modelling (which processes little information) and modelling at the finest available frequency (which may lead to an excessive parameter dimension), and it may also outperform modelling calendar time units (with some months or quarters containing more information than others). We suggest an algorithm that performs an approximate inversion of the inherent seasonal time deformation. We illustrate the procedure using weekly data for temporary staffing services.;

Item Type: IHS Series
Keywords: 'Seasonality' 'Time deformation' 'Prediction' 'Time series'
Classification Codes (e.g. JEL): C22, C53
Status: Published
Date Deposited: 26 Sep 2014 10:39
Last Modified: 25 Jul 2017 07:22
URI: http://irihs.ihs.ac.at/id/eprint/2000

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